As cyber threats continuously grow in sophistication and frequency, companies need to quickly acclimate to effectively detect, respond, and protect their environments. At Intel, we’ve addressed this need by implementing a modern, scalable Cyber Intelligence Platform (CIP) based on Splunk and Apache Kafka. We believe that CIP positions us for the best defense against cyber threats well into the future. Our CIP ingests tens of terabytes of data each day and transforms it into actionable insights through streams processing, context-smart applications, and advanced analytics techniques. Kafka serves as a massive data pipeline within the platform. It achieves economies of scale by acquiring data once and consuming it many times. It reduces technical debt by eliminating custom point-to-point connections for producing and consuming data. At the same time, it provides the ability to operate on data in-stream, enabling us to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). Faster detection and response ultimately lead to better prevention. In our session, we’ll discuss the details described in the IT@Intel white paper that was published in Nov 2020 with same title. We’ll share some stream processing techniques, such as filtering and enriching in Kafka to deliver contextually rich data to Splunk and many of our security controls.